Empirical Study On Industrial Decomposition Method Of Carbon Emissions Cap Control Target Based On Complex Network Perspective

On October 29,2020,“the Proposal of the Central Committee of the Communist Party of China on Formulating the 14 th Five-Year Plan for National Economic and Social Development and the Long-Term Goal for 2030” proposed that it is necessary to formulate an action plan to reach the peak of carbon emissions by 2030 and the implementation of carbon emissions cap control is the guarantee to achieve the the carbon emissions peak.Therefore,Scientific and reasonable prediction and decomposition of the carbon emissions cap control target is of great significance for the early realization of the peak.Most of the existing studies focus on regions and emphasize the synergistic emission reduction effect among regions.In fact,the carbon emissions reduction target ultimately needs to be implemented in the production process of various industries.Carbon emissions will transfer among industries with the flow of production factors,forming a complex linkage network structure,and the synergistic emission reduction effect among industries should not be ignored.The development of machine learning,social network and complex network control science provides a new method to solve the above problems.Therefore,from the perspective of complex network,interdisciplinary research on the decomposition of carbon emissions cap control target at industrial Level is worth exploring.The purpose of this study is to achieve the industrial decomposition of carbon emissions cap control target,constructs the prediction model of inter-industry carbon emissions transfer,industry selection model of carbon emissions reduction control,industrial decomposition model of carbon emissions cap control target and policy research.It mainly includes the following five aspects:firstly,using the non-competitive input-output method to calculate the inter-industry carbon emissions transfer based on the principle of consumer responsibility,so as to build China’s the inter-industry carbon emissions transfer network.The second is to according to the sequence characteristics of inter-industry carbon emissions transfer,and predict China’s inter-industry carbon emissions transfer network from 2020 to 2030.The third is to study the characteristics of network structure and its impact on carbon emissions transfer.The fourth is to find out the exact controllable minimum control industry set with the lowest cost,and take the predicted total amount of carbon emissions transfer among industries in 2020 as the initial control target,study the industrial decomposition of carbon emissions cap control.The fifth is to study the key industries and policy implementation of carbon emissions reduction,and put forward the path optimization strategy of carbon emissions cap control.The innovation of this study is mainly reflected in three aspects: firstly,a general vector machine hybrid prediction model(ROGM-QPSO-GVM)based on small sample random oscillation sequence is proposed.The network parameters of the general vector machine model are optimized by quantum particle swarm optimization algorithm to improve the prediction performance of the model.The second is to introduce the complex network control theory,establish the industry selection model of carbon emissions reduction control,and propose a exact controllable minimum control industry set search algorithm to minimize the cost of carbon emissions reduction,so as to find the minimum control industry set that can realize the exact control of the network in the short term.The third is to build an industrial decomposition model of total amount of carbon emissions transfer control target,and propose an industrial decomposition algorithm of carbon emissions cap control target,so as to obtain the minimum control industry set decomposition scheme under the carbon emissions cap control target in2020.Around the construction,prediction,network structure characteristics,influencing factors and control of China’s inter-industry carbon emissions transfer network,the main conclusions are as follows:(1)The change trend of direct carbon emissions,complete carbon emissions and total amount of carbon emissions transfer is consistent,and the industry ranking of the latter two is relatively close,which is quite different from that of direct carbon emissions,the complete carbon emissions of industry is the result of reallocation of direct carbon emissions among industries through carbon emissions transfer based on the principle of consumer responsibility.From 1997 to 2017,79.95% of the annual average direct carbon emissions were transferred with intermediate products and services.Through this transfer,the inter-industry carbon emissions transfer network can be constructed,network structure characteristics and industry direct carbon emissions intensity and other factors will have an significant impact on carbon emissions transfer.(2)Through the analysis of the prediction results of China’s inter-industry carbon emissions transfer network,it is found that the average edge traffic of network decreases first and then increases,and the network aggregation degree shows an upward trend.The average 15% edges in the network controls about 90% of the carbon emissions transfer volume.The degree of correlation between manufacturing industries is increasing,and the proportion of carbon emissions transfer in the whole industry is increasing.The amount of inter-industry carbon emissions transfer changes significantly,The ranking of various industries in the network fluctuates,but the overall change is not big.The key industries in the network have changed,but the overall difference is not big.The industry group structure of the network is stable.(3)Based on China’s inter-industry carbon emissions transfer network in 2017,under the carbon emissions cap control target of reducing direct carbon emissions by 8.84%in 2020,the emission reduction targets of 15 carbon emissions reduction control industries should be set between 1.92% and 13.48%,and other 13 industries will be indirectly controlled by policies,the emission reduction proportion will be between0.001% and 9.42%.The results show that,compared with the industry wide control scheme,controlling the minimum control industry set is also an effective policy choice.We should follow the “short-term industrial emission reduction path of implementing carbon emissions cap control based on the combination of network controllable‘consumer end’ control industry classification control and cross-industry collaborative emission reduction”,through such strategies as the stage setting of carbon emissions cap control target,the gradual expand of carbon emissions reduction control industry scope,the completeness of industry carbon emissions monitoring system and the flexibility of target responsibility assessment,the coordination of policy tools and the matching of capacity building,the path of medium and long-term carbon emissions cap control in China is optimized to ensure the realization of carbon emissions peak by 2030.